Effectively searching for oil and gas reservoirs often requires imaging the reservoirs using three-dimensional (3-D) seismic data. Seismic data is recorded at the earth's surface or in wells, and an accurate model of the underlying geologic structure is constructed by processing the data. Imaging 3-D seismic data is perhaps the most computationally intensive task facing the oil and gas industry today. The size of typical 3-D seismic surveys can be in the range of hundreds of gigabytes to tens of terabytes of data. Processing such large amounts of data often poses serious computational challenges.
Obtaining high-quality earth images necessary for contemporary reservoir development and exploration is particularly difficult in areas with complex geologic structures. In such regions, conventional seismic technology may either incorrectly reconstruct the position of geological features or create no usable image at all. Moreover, as old oil fields are depleted, the search for hydrocarbons has moved to smaller reservoirs and increasingly hostile environments, where drilling is more expensive. Advanced imaging techniques capable of providing improved knowledge of the subsurface detail in areas with complex geologic structures are becoming increasingly important.
Many imaging techniques, such as techniques based on Kirchhoff migration, require computing traveltimes for the region of interest. Efficiently applying such imaging techniques to 3-D seismic information requires fast, robust, and accurate methods to compute traveltimes.
Commonly used traveltime computation techniques face a number of challenges. Ray tracing methods, while relatively accurate, often suffer from considerable complexity. Finite-difference schemes are typically simpler computationally, but often suffer from stability and accuracy issues. In particular, currently available finite-difference schemes often fail to adequately handle complex propagation effects in fields where complex geology and associated anomalous elastic variations are present.
A fast, accurate and unconditionally stable 3-D traveltime computation method would be an important tool in the arsenal of the seismic imaging geophysicist. A robust traveltime computation technique could be useful in many seismic data processing methods, including migration, datuming, modeling, and data acquisition design. Such a technique would allow improved use of three-dimensional (3-D) seismic data to characterize and delineate reservoirs and to monitor enhanced oil recovery (EOR) processes. A fast and robust traveltime computation method would be particularly useful for characterizing extremely complicated geological conditions such as those that exist below layers of salt in the Gulf of Mexico and in the overthrust regions of the Western United States. Better seismic images of complex subsurface geology can reduce development costs, as well as increase the amount of hydrocarbons recovered and the amount of national oil reserves.